Global population genetic dynamics of a highly migratory, apex predator shark
Bibliographic record
Abstract
Abstract Knowledge of genetic connectivity dynamics in the world's large‐bodied, highly migratory, apex predator sharks across their global ranges is limited. One such species, the tiger shark (Galeocerdo cuvier), occurs worldwide in warm temperate and tropical waters, uses remarkably diverse habitats (nearshore to pelagic) and possesses a generalist diet that can structure marine ecosystems through top‐down processes. We investigated the phylogeography and the global population structure of this exploited, phylogenetically enigmatic shark by using 10 nuclear microsatellites (n = 380) and sequences from the mitochondrial control region (CR, n = 340) and cytochrome oxidase I gene (n = 100). All three marker classes showed the genetic differentiation between tiger sharks from the western Atlantic and Indo‐Pacific ocean basins (microsatellite FST > 0.129; CR ΦST > 0.497), the presence of North vs. southwestern Atlantic differentiation and the isolation of tiger sharks sampled from Hawaii from other surveyed locations. Furthermore, mitochondrial DNA revealed high levels of intraocean basin matrilineal population structure, suggesting female philopatry and sex‐biased gene flow. Coalescent‐ and genetic distance‐based estimates of divergence from CR sequences were largely congruent (dcorr = 0.0015–0.0050), indicating a separation of Indo‐Pacific and western Atlantic tiger sharks <1 million years ago. Mitochondrial haplotype relationships suggested that the western South Atlantic Ocean was likely a historical connection for interocean basin linkages via the dispersal around South Africa. Together, the results reveal unexpectedly high levels of population structure in a highly migratory, behaviourally generalist, cosmopolitan ocean predator, calling for management and conservation on smaller‐than‐anticipated spatial scales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".